{"id":"W2472270219","doi":"10.1016/j.meatsci.2016.06.031","title":"Accuracy of dual energy X-ray absorptiometry (DXA) in assessing carcass composition from different pig populations","year":2016,"lang":"en","type":"article","venue":"Meat Science","topic":"Body Composition Measurement Techniques","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan; Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada; Alberta Livestock and Meat Agency","keywords":"Dual-energy X-ray absorptiometry; Dual energy; Composition (language); Dual purpose; Animal science; Biology; Medicine; Internal medicine; Bone mineral; Osteoporosis","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003648954,0.0001210856,0.0002363038,0.000601295,0.0001108079,0.0000430874,0.0001750229,0.00005261129,0.00008022249],"category_scores_gemma":[0.0001503293,0.0000843327,0.00004915659,0.0007593175,0.0003209307,0.0005350083,0.00007516249,0.0000792787,0.000004186563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003006109,"about_ca_system_score_gemma":0.0001094374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003532526,"about_ca_topic_score_gemma":0.00005078718,"domain_scores_codex":[0.9981775,0.00007234563,0.0003479597,0.0003309526,0.0008397586,0.0002315156],"domain_scores_gemma":[0.9990427,0.0001311146,0.0001506813,0.0003628842,0.0002035112,0.0001091197],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00001514357,0.0001535413,0.1027641,0.000005816735,0.000003346649,0.000005023503,0.00004395706,0.000003793331,0.8905643,0.001224818,0.00004056671,0.005175584],"study_design_scores_gemma":[0.0004302711,0.00005701649,0.5524907,0.0003736524,0.00001552277,0.000004781402,0.00001741393,0.0003597901,0.4453575,0.0007887038,0.00002592417,0.00007881589],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9446149,0.00006912604,0.05337123,0.0008254659,0.0001635887,0.0001443381,0.00001215554,0.00008470449,0.0007144491],"genre_scores_gemma":[0.9926891,0.00001365072,0.007068075,0.0001075419,0.00006066285,0.00001245406,0.0000161143,0.000009253797,0.00002310973],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4497265,"threshold_uncertainty_score":0.3438987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06533396656276179,"score_gpt":0.3432543291217831,"score_spread":0.2779203625590213,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}